Advancements in Arrhythmia Classification: A Comprehensive Survey of AI Techniques

This comprehensive survey presents an in-depth exploration of arrhythmia classification techniques, spanning from traditional machine learning approaches to deep learning models and hybrid methodologies. The survey covers the fundamental importance of accurate arrhythmia diagnosis, highlighting its critical role in cardiovascular disease management. Each techniques advantages, disadvantages, and applications are documented. The focus is on the evolution of deep learning from feature extraction to automatic learning and validates its adaptableness to solving complex problems derived from electrocardiogram signals. Future developments and understanding the concept of cardiac arrhythmia is the goal of this paper, by exploiting the technology, current challenges, and results of the literature.